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HR Tech 2026 Agenda

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AI Lab: The Hidden Driver of Frontline Turnover

23 Apr 2026
Get Connected - AI Users Lab
AI Labs

Frontline turnover is often treated as a hiring or engagement problem. In reality, everyday scheduling decisions quietly shape employee experience, fairness, and trust.

When managers build schedules manually under time pressure, patterns of unfairness can emerge — the same employees working more weekends, closing late and opening early, or receiving less flexibility around personal commitments. Over time, this erodes trust, increases fatigue, and drives preventable turnover.

In this interactive AI Lab, Tim, Solution Engineer at Quinyx, will demonstrate how organisations can detect these hidden drivers of churn. Through a live simulation, he will show how AI helps identify patterns such as uneven shift distribution, repeated weekend work, and workload imbalance.

Participants will join guided discussions, share experiences, and learn from peers how organisations can improve fairness, strengthen employee experience, and reduce frontline turnover.

Topic

AI Automation & Agentic Systems

Learning Objective 1:

Identify how scheduling practices — such as uneven shift distribution, last-minute changes, and unconscious manager bias — contribute to frontline turnover and disengagement.

Learning Objective 2:

Evaluate how perceived fairness in scheduling affects employee experience, retention, and team stability in frontline operations.

Learning Objective 3:

Apply practical guardrails for fairer scheduling — including fairness rules, preference visibility, and workload balance — that HR teams can implement to support managers and reduce preventable churn.